Executive Technical Recruiter at LHH, a Forbes 2024 "America's Best" global talent solutions firm. LHH has a dynamic and challenging opportunity for a Principal Data & AI Scientist to join our client's team. In this role, you will be responsible for designing, developing, and operationalizing advanced data science, machine learning, and AI solutions across core insurance domains such as underwriting, claims automation, pricing optimization, risk modeling, and customer lifecycle personalization. Location: Candidates must live in one of the following states: WA, OR, ID, OH, SC, TX, or FL. Salary & Benefits: $160k to $190k annually (depending on location & experience) Medical, dental, and vision insurance 401(k) plan with employer match Vacation time accrues at a rate of 10 days annually, with increases based on a tenure schedule, up to a maximum of 25 days per year. PTO included Four (4) personal days are granted immediately upon hire. Paid holidays are provided for the eight (8) holidays observed in this role throughout the calendar year. Up to ten (10) days of sick leave are granted immediately upon hire (pro-rated based on hire date and full-time/part-time status). Additional paid time off is available for bereavement, jury duty, and employee volunteer activities in the community. Life and disability insurance Qualifications: Experience: Bachelor’s degree (B.A. or B.S.) or equivalent work experience in a related field such as Computer Science, Software Engineering, Artificial Intelligence, Machine Learning, Data Science, or Data Engineering. Minimum of 10 years of enterprise-scale experience in designing, implementing, and deploying AI/ML models. At least 7 years of experience working with cloud-based AI platforms, including Azure Machine Learning, Databricks, and Snowflake. 7+ years of hands-on experience implementing both supervised and unsupervised learning techniques in real-world applications. Experience in the insurance industry, specifically in Auto, Home, and Umbrella insurance processes, including underwriting, claims analysis, and risk assessment. Strong experience in natural language processing (NLP) and generative AI applications. Expertise in MLOps, model lifecycle management, and large-scale AI model deployment. Proficient in Python, PySpark, and SQL. Deep understanding of Azure Databricks, Delta Lake, Unity Catalog, Azure Synapse Analytics, and Azure Data Factory. Experience with distributed model training and serving on Databricks. Hands-on experience with Gen AI, RAG pipelines, Vector Databases, and Knowledge Graphs. Strong problem-solving skills and a deep understanding of statistical and mathematical principles. Expertise in both supervised and unsupervised learning techniques, with the ability to implement AI/ML solutions that enhance data-driven decision-making in the insurance industry. Industry Knowledge: Experience working with advanced AI frameworks such as LangChain, LlamaIndex, and Hugging Face transformers (preferred). Familiarity with Azure OpenAI, LLM fine-tuning, or cognitive services (preferred). Familiarity with agile software delivery methodologies such as Scrum. Preferred Qualifications: Master’s degree or Ph.D. in a related field such as Artificial Intelligence, Data Science, or Machine Learning. Responsibilities: Lead the development and deployment of AI models utilizing both supervised and unsupervised learning techniques. Design, implement, and optimize Retrieval-Augmented Generation (RAG) pipelines for AI-driven decision support. Leverage Vector Databases and Knowledge Graphs to enhance AI applications in underwriting, claims processing, and customer engagement. Develop robust data pipelines for ingestion, transformation, and storage to support AI/ML workloads. Design and implement scalable solutions using cloud-based AI platforms such as Azure Machine Learning, Databricks, and Snowflake. Implement MLOps best practices, including CI/CD for model training, validation, deployment, and monitoring. Develop generative AI models to deliver personalized customer experiences and automate complex decision-making processes. Apply natural language processing (NLP) techniques to analyze and extract insights from unstructured data sources. Optimize AI models for performance, scalability, and reliability in enterprise environments. Conduct architecture design reviews and performance tuning for AI/ML applications. Collaborate cross-functionally with business and technology teams to identify AI-driven opportunities and define strategies. Ensure compliance with ethical AI principles, model governance, and data privacy regulations. Demonstrate behaviors consistent with policies, values, code of ethics, and business conduct. Authentically support the company brand and actively seek top talent to help achieve the company mission statement. Provide guidance, mentorship, knowledge sharing, and technical growth to team members. Perform other duties as assigned. Equal Opportunity Employer/Veterans/Disabled To read our Candidate Privacy Information Statement, which explains how we will use your information, please navigate to https://www.lhh.com/us/en/candidate-privacy The Company will consider qualified applicants with arrest and conviction records in accordance with federal, state, and local laws and/or security clearance requirements, including, as applicable: California Fair Chance Act Los Angeles City Fair Chance Ordinance Los Angeles County Fair Chance Ordinance for Employers San Francisco Fair Chance Ordinance Seniority level Mid-Senior level Employment type Full-time Job function Information Technology Industries Insurance End of description

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